Variance-based SEM, also known under the term partial least squares (PLS) analysis, is an approach that has gained increasing interest among marketing researchers in recent years. During the last 25 years, more than 30 articles have been published in leading marketing journals that have applied this approach instead of the more traditional alternative of covariance-based SEM (CBSEM). However, although an analysis of these previous publications shows that there seems to be at least an implicit agreement about the factors that should drive the choice between PLS analysis and CBSEM, no research has until now empirically compared the performance of these approaches given a set of different conditions. Our study addresses this open question by conducting a large-scale Monte-Carlo simulation. We show that justifying the choice of PLS due to a lack of assumptions regarding indicator distribution and measurement scale is often inappropriate, as CBSEM proves extremely robust with respect to violations of its underlying distributional assumptions. Additionally, CBSEM clearly outperforms PLS in terms of parameter consistency and is preferable in terms of parameter accuracy as long as the sample size exceeds a certain threshold (250 observations). Nevertheless, PLS analysis should be preferred when the emphasis is on prediction and theory development, as the statistical power of PLS is always larger than or equal to that of CBSEM; already, 100 observations can be sufficient to achieve acceptable levels of statistical power given a certain quality of the measurement model.

An understanding of how to manage relationships with customers effectively has become an important topic for both academicians and practitioners in recent years. However, the existing academic literature and the practical applications of customer relationship management (CRM) strategies do not provide a clear indication of what specifically constitutes CRM processes. In this study, the authors (1) conceptualize a construct of the CRM process and its dimensions, (2) operationalize and validate the construct, and (3) empirically investigate the organizational performance consequences of implementing CRM processes. Their research questions are addressed in two cross-sectional studies across four different industries and three countries. The first key outcome is a theoretically sound CRM process measure that outlines three key stages: initiation, maintenance, and termination. The second key result is that the implementation of CRM processes has a moderately positive association with both perceptual and objective company performance.

Relationship marketing emphasizes the need for maintaining long-term customer relationships. It is beneficial, in general, to serve customers over a longer time, especially in a contractual relationship. However, it is not clear whether some of the findings observed in a contractual setting hold good in noncontractual scenarios: relationships between a seller and a buyer that are not governed by a contract or membership. The authors offer four different propositions in this study and subsequently test each one in a noncontractual context. The four propositions relate to whether (1) there exists a strong positive customer lifetime-profitability relationship, (2) profits increase over time, (3) the costs of serving long-life customers are less, and (4) long-life customers pay higher prices. The authors develop arguments both for and against each of the propositions. The data for this study, obtained from a large catalog retailer, cover a three-year window and are recorded on a daily basis. The empirical findings observed in this study challenge all the expectations derived from the literature. Long-life customers are not necessarily profitable customers. The authors develop plausible explanations for findings that go against the available evidence in the literature and identify three indicators through discriminant analysis that can help managers focus their efforts on more profitable customers. The authors draw several marketing implications and acknowledge the limitations of the study.

International audienceThis article examines key success factors for designing and delivering combinations of goods and services (i.e., hybrid offerings) in business markets. Goods manufacturers, unlike pure service providers, find themselves in a unique position to grow revenues through hybrid offerings but must learn how to leverage unique resources and build distinctive capabilities. Using case studies and depth interviews with senior executives in manufacturing companies, the authors develop a resource-capability framework as a basis for research and practice. Executives identify four critical resources: (1) product usage and process data derived from the firm's installed base of physical goods, (2) product development and manufacturing assets, (3) an experienced product sales force and distribution network, and (4) a field service organization. In leveraging these specific resources, successful firms build five critical capabilities: (1) service-related data processing and interpretation capability, (2) execution risk assessment and mitigation capability, (3) design-to-service capability, (4) hybrid offering sales capability, and (5) hybrid offering deployment capability. These capabilities influence manufacturers' positional advantage in two directions: differentiation and cost leadership. The authors propose a new typology of industrial services and discuss how resources and capabilities affect success across categories of hybrid offers

The authors develop a framework that incorporates projected profitability of customers in the computation of lifetime duration. Furthermore, the authors identify factors under a manager's control that explain the variation in the profitable lifetime duration. They also compare other frameworks with the traditional methods such as the recency, frequency, and monetary value framework and past customer value and illustrate the superiority of the proposed framework. Finally, the authors develop several key implications that can be of value to decision makers in managing customer relationships.

Since 2000, customer management (CM) research has evolved and has had a significant impact on the marketing discipline. In an increasingly networked society where customers can interact easily with other customers and firms through social networks and other new media, the authors propose that customer engagement is an important new development in CM. Customer engagement is considered as a behavioral manifestation toward the brand or firm that goes beyond transactions. The authors propose a conceptual model of the antecedents, impediments, and firm consequences of customer engagement and relate this model to seven articles appearing in the special issue on customer engagement.

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One of the most important tasks in marketing is to create and communicate value to customers to drive their satisfaction, loyalty, and profitability. In this study, the authors assume that customer value is a dual concept. First, in order to be successful, firms (and the marketing function) have to create perceived value for customers. Toward that end, marketers have to measure customer perceived value and have to provide customer perceptions of value through marketing-mix elements. Second, customers in return give value through multiple forms of engagement (customer lifetime value, in the widest sense) for the organization. Therefore, marketers need to measure and manage this value of the customer(s) to the firm and have to incorporate this aspect into real-time marketing decisions. The authors integrate and synthesize existing findings, show the best practices of implementation, and highlight future research avenues.